Providing a mask for a patient based on a temporal model generated from a plurality of facial scans

ABSTRACT

A method for identifying a mask for a patient includes: receiving a plurality of images of a patient&#39;s face; analyzing the plurality of images to generate a temporal model of the patient&#39;s face, determining a mask for the patient using the temporal model of the patient&#39;s face, and identifying the mask to the patient.

CROSS-REFERENCE TO RELATED APPLICATIONS

This patent application claims the priority benefit under 35 U.S.C. §119(e) of U.S. Provisional Application No. 62/565,304 filed on Sep. 29,2017, the contents of which are herein incorporated by reference.

BACKGROUND OF THE INVENTION 1. Field of the Invention

The present invention pertains to methods for identifying a custom maskfor a patient for use in receiving a flow of a treatment gas to theairway of the patient. The present invention also pertains to systemsfor carrying out such methods.

2. Description of the Related Art

Many individuals suffer from disordered breathing during sleep. Sleepapnea is a common example of such sleep disordered breathing suffered bymillions of people throughout the world. One type of sleep apnea isobstructive sleep apnea (OSA), which is a condition in which sleep isrepeatedly interrupted by an inability to breathe due to an obstructionof the airway; typically the upper airway or pharyngeal area.Obstruction of the airway is generally believed to be due, at least inpart, to a general relaxation of the muscles which stabilize the upperairway segment, thereby allowing the tissues to collapse the airway.Another type of sleep apnea syndrome is a central apnea, which is acessation of respiration due to the absence of respiratory signals fromthe brain's respiratory center. An apnea condition, whether obstructive,central, or mixed, which is a combination of obstructive and central, isdefined as the complete or near cessation of breathing, for example a90% or greater reduction in peak respiratory air-flow.

Those afflicted with sleep apnea experience sleep fragmentation andcomplete or nearly complete cessation of ventilation intermittentlyduring sleep with potentially severe degrees of oxyhemoglobindesaturation. These symptoms may be translated clinically into extremedaytime sleepiness, cardiac arrhythmias, pulmonary-artery hypertension,congestive heart failure and/or cognitive dysfunction. Otherconsequences of sleep apnea include right ventricular dysfunction,carbon dioxide retention during wakefulness, as well as during sleep,and continuous reduced arterial oxygen tension. Sleep apnea sufferersmay be at risk for excessive mortality from these factors as well as byan elevated risk for accidents while driving and/or operatingpotentially dangerous equipment.

Even if a patient does not suffer from a complete or nearly completeobstruction of the airway, it is also known that adverse effects, suchas arousals from sleep, can occur where there is only a partialobstruction of the airway. Partial obstruction of the airway typicallyresults in shallow breathing referred to as a hypopnea. A hypopnea istypically defined as a 50% or greater reduction in the peak respiratoryair-flow. Other types of sleep disordered breathing include, withoutlimitation, upper airway resistance syndrome (UARS) and vibration of theairway, such as vibration of the pharyngeal wall, commonly referred toas snoring.

It is well known to treat sleep disordered breathing by applying acontinuous positive air pressure (CPAP) to the patient's airway. Thispositive pressure effectively “splints” the airway, thereby maintainingan open passage to the lungs. It is also known to provide a positivepressure therapy in which the pressure of gas delivered to the patientvaries with the patient's breathing cycle, or varies with the patient'sbreathing effort, to increase the comfort to the patient. This pressuresupport technique is referred to as bi-level pressure support, in whichthe inspiratory positive airway pressure (IPAP) delivered to the patientis higher than the expiratory positive airway pressure (EPAP). It isfurther known to provide a positive pressure therapy in which thepressure is automatically adjusted based on the detected conditions ofthe patient, such as whether the patient is experiencing an apnea and/orhypopnea. This pressure support technique is referred to as anauto-titration type of pressure support, because the pressure supportdevice seeks to provide a pressure to the patient that is only as highas necessary to treat the disordered breathing.

Pressure support therapies as just described involve the placement of apatient interface device including a mask component having a soft,flexible sealing cushion on the face of the patient. The mask componentmay be, without limitation, a nasal mask that covers the patient's nose,a nasal/oral mask that covers the patient's nose and mouth, or a fullface mask that covers the patient's face. Such patient interface devicesmay also employ other patient contacting components, such as foreheadsupports, cheek pads and chin pads. The patient interface device istypically secured to the patient's head by a headgear component. Thepatient interface device is connected to a gas delivery tube or conduitand interfaces the pressure support device with the airway of thepatient, so that a flow of breathing gas can be delivered from thepressure/flow generating device to the airway of the patient.

Current state-of-the-art systems for creating a “custom” mask for apatient for use in delivering a flow of a treatment gas to the patientuse a single 3-dimensional (3-D) scan as input to create a spatialmodel, which is set as a reference for creating the custom mask. Anexample of such a 3-D scan 10 of the face of a patient is shown inFIG. 1. In such systems, the user is subjected to a neutral faceexpression during image acquisition from which the possible facegeometry is extracted by determining the location of a plurality offacial landmarks or points (labeled A-W) for mask design. However, suchapproach fails, as variations in the user's facial geometry inunconstrained poses are not considered during such a neutral scanacquisition. Accordingly, the generated mask does not accommodate to thevariations in face geometry resulting from movement of the patient'sface, which then becomes a problem with comfort and stability. Moreparticularly, face variations which would commonly occur during sleepare not assessed in such 3-D scans, which makes the custom mask creationmore difficult to accommodate the user's actual unconstrained facialgeometry.

SUMMARY OF THE INVENTION

As one aspect of the invention a method for identifying a mask for apatient is provided. The method comprises: receiving a plurality ofimages of a patient's face; analyzing the plurality of images togenerate a temporal model of the patient's face; determining a mask forthe patient using the temporal model of the patient's face; andidentifying the mask to the patient.

Identifying the mask to the patient may comprise providing the patientwith a specification of the mask or may comprise providing the patientwith the mask.

Receiving a plurality of images may comprise receiving a plurality of3-D images of the patient's face and analyzing the plurality of imagesmay comprise generating the temporal model from the plurality of 3-Dimages. The plurality of 3-D images may comprise a sequence of 3-Dimages captured over time. Analyzing the plurality of images maycomprise: determining an expected range of facial geometries expressedby the patient's face; registering the range of facial geometries tocreate the temporal model; and determining an operating range of facialdimensions of the patient, wherein determining the appropriate mask forthe patient based on the analysis of the plurality of 3-D imagescomprises determining an appropriate mask for the patient based on theoperating range of facial dimensions. Determining an expected range offacial geometries expressed by the patient's face may comprisedetermining the positions of a plurality of facial landmarks in the 3-Dimages.

Receiving a plurality of 3-D images of the patient's face comprisescapturing the plurality of 3-D images with a 3-D scanning device.

The plurality of 3-D images may comprise one or more of the patient'sface in a plurality of predetermined poses, the patient's face in aplurality of natural poses, and the patient's face in a plurality ofdiffering expressions.

The temporal model may comprise a range of facial dimensions andgeometries of the patient's face and determining a mask for the patientmay comprise comparing the range of facial dimensions and geometries toestablish an operating range of masks.

Receiving a plurality of images may comprise receiving one or more 3-Dimages of the patient's face and a plurality of 2-D images of thepatient's face. Analyzing the plurality of images may comprise:generating a 3-D spatial model of the patient's face by analyzing theone or more 3-D images; and generating the temporal model of thepatient's face by registering the plurality of 2-D images to the 3-Dspatial model. The plurality of 2-D images may comprise the patient'sface in one or more of: a plurality of predetermined poses, a pluralityof natural poses, and a plurality of differing expressions. The methodmay further comprise: extracting information from the plurality of 2-Dimages, the information including at least one: of landmarks,orientation, and features; and refining the generated 3-D spatial modelusing the extracted information.

Receiving a plurality of images may comprise receiving a plurality of2-D images of the patient's face. Analyzing the plurality of imagescomprises: generating a plurality of 3-D models from the plurality of2-D images by using standard photogrammetric techniques or disparitymaps; and generating the temporal model of the patient's face byregistering the 3-D models. The plurality of 2-D images include imagesof the patient's face in one or more of: a plurality of predeterminedposes, a plurality of natural poses, and a plurality of differingexpressions.

Receiving a plurality of images comprises receiving a plurality of 2-Dimages of the patient's face which each contain a reference object ofknown size and analyzing the plurality of images may comprise generatingthe temporal model of the patient's face using the plurality of 2-Dimages.

Receiving a plurality of images comprises receiving a plurality of 2-Dimages of the patient's face, wherein each 2-D image was captured with aknown distance between a device used to capture the 2-D image and thepatient's face; and wherein analyzing the plurality of images maycomprise generating the spatial and temporal models of the patient'sface using the plurality of 2-D images.

As another aspect of the present invention, a system for identifying amask for a patient is provided. The system comprises: a processing unit;and an output device in communication with the processing unit, whereinthe processing unit is programmed to: receive a plurality of images ofthe patient's face; analyze the plurality of images to generate atemporal model of the patient's face; determine a mask for the patientusing the temporal model of the patient's face; and identify the mask tothe patient via the output device. The output device may comprise a 3-Dprinter.

The system may further comprise an image capturing device incommunication with the processing unit, the image capturing devicestructured to capture the plurality of images of the patient's face. Theimage capturing device may comprise a 3-D scanner.

These and other objects, features, and characteristics of the presentinvention, as well as the methods of operation and functions of therelated elements of structure and the combination of parts and economiesof manufacture, will become more apparent upon consideration of thefollowing description and the appended claims with reference to theaccompanying drawings, all of which form a part of this specification,wherein like reference numerals designate corresponding parts in thevarious figures. It is to be expressly understood, however, that thedrawings are for the purpose of illustration and description only andare not intended as a definition of the limits of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an example of a 3-D facial scan obtained in accordance with aprior art approach for mask selection;

FIG. 2 is a schematic diagram of a system for use in providing a maskfor a patient in accordance with an exemplary embodiment of the presentinvention;

FIG. 3 is a flowchart showing a method for providing a mask for apatient in accordance with an exemplary embodiment of the presentinvention; and

FIG. 4 is a plurality of 3-D scans of a patient obtained in accordancewith an exemplary embodiment of the present invention.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

As required, detailed embodiments of the present invention are disclosedherein; however, it is to be understood that the disclosed embodimentsare merely exemplary of the invention, which may be embodied in variousforms. Therefore, specific structural and functional details disclosedherein are not to be interpreted as limiting, but merely as a basis forthe claims and as a representative basis for teaching one skilled in theart to variously employ the present invention in virtually anyappropriately detailed structure.

As used herein, the singular form of “a”, “an”, and “the” include pluralreferences unless the context clearly dictates otherwise. As usedherein, the statement that two or more parts or components are “coupled”shall mean that the parts are joined or operate together either directlyor indirectly, i.e., through one or more intermediate parts orcomponents, so long as a link occurs. As used herein, “directly coupled”means that two elements are directly in contact with each other. As usedherein, “fixedly coupled” or “fixed” means that two components arecoupled so as to move as one while maintaining a constant orientationrelative to each other.

As used herein, the word “unitary” means a component is created as asingle piece or unit. That is, a component that includes pieces that arecreated separately and then coupled together as a unit is not a“unitary” component or body. As used herein, the statement that two ormore parts or components “engage” one another shall mean that the partsexert a force against one another either directly or through one or moreintermediate parts or components. As used herein, the term “number”shall mean one or an integer greater than one (i.e., a plurality).

Directional phrases used herein, such as, for example and withoutlimitation, top, bottom, left, right, upper, lower, front, back, andderivatives thereof, relate to the orientation of the elements shown inthe drawings and are not limiting upon the claims unless expresslyrecited therein. As used herein, the term “facial landmark” shall referto particular points on a human face associated with elements of theface. Examples of facial landmarks may include, without limitation, apoint at the tip of the nose; points at edges of the eyes or mouth, etc.

As used herein, the term “temporal model” shall refer to a numericrepresentation of an object which includes both three dimensionalinformation as well as time-based variations thereof. For example, atemporal model of a face includes information regarding positioning offacial landmarks, surface geometry and texture of the face, both withrespect to a fixed point as well as relative to other facial landmarks,geometry, or both. As used herein, the term “image” shall refer to arepresentation of the form of a person or thing. Such representation maybe a reproduction of the form or may be in the form of electronicinformation describing the form.

As used herein, the term “2-D image” shall refer to a two-dimensionalrepresentation of the form of a person or thing, whether in electronicform (e.g., such as stored in digital memory) or in visible form (e.g.,displayed via an electronic display). A 2-D image may be captured of aphysical object by using a digital camera or 2-D scanning device. Asused herein, the term “3-D image” shall refer to a three-dimensionalrepresentation of the form of a person or thing, whether in electronicform (e.g., such as stored in digital memory) or in visible form (e.g.,displayed via a holographic projector). A 3-D image may be captured of aphysical object by using a 3-D scanning device.

As used herein, the term “image registration”, also referred to as“registering” is the process of aligning two or more images of the samescene. This process involves designating one image as the referenceimage, also called the fixed image, and applying geometrictransformations or local displacements to the other images so that theyalign with the reference. By applying image registration to a series of3-D images, time based changes to the 3-D images are readily obtainedfor use in a temporal model (i.e., a 3-D model also having informationregarding changes occurring over time).

In overcoming shortcomings of prior art approaches which utilize asingle 2-D or 3-D image for creating “custom mask”, embodiments of thepresent invention utilize series of expressions (i.e. multiple 2-D or3-D images) to generate a temporal model of the patient's face thatincludes not only 3-D spatial information but also time-basedinformation in regards there to. With such temporal information, a wideoperating range of facial geometries is determined which can then beutilized for designing a custom mask, or selecting a pre-made mask fromamongst a plurality of masks, which provides maximum comfort andstability for the patient. Additionally, time-based analysis (e.g.,velocity/acceleration of facial landmarks) can indicate the nature offacial movement (i.e., was it a conscious or unconscious movement or wasit a facial expression) which can be used as a criteria to predict anormal operating range of facial geometry during sleep.

FIG. 2 is a schematic diagram of a system 20 which may be employed incarrying out methods described herein below. System 20 includes an imagecapturing device 22 for capturing images of a patient's face. As will beappreciated from the examples discussed further herein image capturingdevice 22 may be one or more of a digital camera structured to capture2-D images of an object, a scanner structured to capture 3-D scans of anobject, or any other suitable device for capturing 2 or 3 dimensionalimages of an object, which in the present matter would be a patient'sface. System 20 also includes a processing unit 24 in communication withimage scanning device 22 and an output device 26 in communication withprocessing device 24. System 20 may also include an input device 28 incommunication with processing device 24 for inputting of information toprocessing unit 24. Alternately, output device 26 may be in the form ofa combination input/output device (e.g., without limitation, atouchscreen) for both inputting information to, and receivinginformation from, processing unit 24.

Processing unit 24 includes a processing portion which may be, forexample, a microprocessor, a microcontroller or some other suitableprocessing device, and a memory portion that may be internal to theprocessing portion or operatively coupled to the processing portion andthat provides a storage medium for data and software executable by theprocessing portion for controlling the operation of system 20.

Processing unit 24 includes a processor 30, a memory 32, and acommunication unit 34. Processor 30 may form all or part of a processingportion which may be, for example, a microprocessor, a microcontrolleror some other suitable processing device. Memory 32 may form all or partof a memory portion that may be internal to the processing portion oroperatively coupled to the processing portion and provide a storagemedium for data and software executable by the processing portion forimplementing functionality of processing unit 24. Memory 32 can be anyof one or more of a variety of types of internal and/or external storagemedia such as, without limitation, RAM, ROM, EPROM(s), EEPROM(s), FLASH,and the like that provide a storage register, i.e., a machine readablemedium, for data storage such as in the fashion of an internal storagearea of a computer, and can be volatile memory or nonvolatile memory.

Communication unit 34 may provide for communication between processingunit 24 and other components of system 20 or other external devices viathe internet, cellular, WiFi, wired telephone line, or any othersuitable means. For example, without limitation, communication unit 34may facilitate communication with electronic devices such as a phone,tablet, computer, or other devices whether local or distant, directly orvia a network. Communication facilitated by communication unit 34 mayallow processing unit 24 to send and/or receive data from the componentor device with which it communicates.

FIG. 3 is a flow chart showing basic steps of a method 40 in accordancewith an example embodiment of the present invention, for identifyingand/or providing a particular mask for a given patient that could becarried out, for example, without limitation, by all or some thecomponents of system 20. Method 40 begins at 42 wherein a plurality ofimages of the patient's face are one or both of: captured by an imagecapturing device such as image capturing device 22 of FIG. 2, orreceived by processing unit 24 from an outside source which haspreviously captured such images of the patient's face. The plurality ofimages may comprise 2-D images, 3-D images, or combinations thereof.

As previously discussed, embodiments of the present invention seek toutilize images which represent ranges of facial geometries of thepatient's face. FIG. 4 shows an example of a plurality of such images,labeled A-J, according to an example of the present invention.Accordingly, the plurality of images, regardless of whether they arecaptured as 2-D or 3-D images, may include the patient's face in aplurality of predetermined poses. Some examples of such predeterminedposes may include, for example, without limitation, having the patientpose with an open mouth, a closed mouth, open eyes, closed eyes, lookingin various directions, facing in different directions (e.g., left,right, up, down,) etc. As another example, the plurality of images mayinclude the patient's face in a plurality of natural poses. Such naturalposes may be captured, for example, without limitation, by having thepatient generally be themselves without striking any fixed poses while asequence of images is captured. In yet another example, the plurality ofimages may include the patient's face in a plurality of differingexpressions, for example, without limitation, smiling, frowning,grimacing, pouting, etc.

Next, at 44 the plurality of images or analyzed in order to generate atemporal model of the patient's face. Such generation of a temporalmodel may be accomplished in various ways depending on the type ofimages received/captured at 42. For example, in an embodiment wherein aplurality of 3-D images captured over time are utilized, the temporalmodel may be obtained by registering 3-D images using known imageregistration methods.

As another example, one or more 3-D images may be utilized along with aplurality of 2-D to generate the temporal model. In such example, a 3-Dspatial model of the patient's face is generated using the one or more3-D images. The temporal model is then generated by registering theplurality of 2-D images to the 3-D spatial model. Additionally, in suchexample, information extracted from the plurality of 2-D images,including landmarks, orientation, and features, may be used to refinethe generated 3-D spatial models.

As yet another example, a plurality of 2-D images may be utilized togenerate the temporal model. Such 2-D images may include a referenceobject of known size or be captured from a device with known distancebetween the image capture device and the patient's face. 2-D images withknown size can be used directly (without ever creating a 3-D spatialmodel) to create a temporal model that is 2-D+time. The 2-D spatialmodel can be analyzed in much the same way as the 3D spatial model (e.g.by calculating ranges for the inter-landmark distances). Alternatively,2-D images of known size could be used to approximate a 3D spatialmodel, for example by morphing a 3-D template to fit the 2-D images.Alternatively, 2D images could be used to create a 3-D spatial modelusing any number of techniques known to one skilled in the art such asthrough the use of disparity maps in the epipolar plane, volumetric deepneural networks (DNN), or generative adversarial network correlations.In another approach, a plurality of 3-D models is generated from theplurality of 2-D images by using standard photogrammetric techniques.The temporal model is then generated by registering the 3-D models.

Once the temporal model has been generated, the temporal model, and moreparticularly the information regarding the range or ranges of facialexpressions contained therein, are used in determining a mask for thepatient. Depending on various factors such as, for example, withoutlimitation, time, budget, particular application, such determination mayresult in determining a design for a custom mask or a determination ofan existing mask from amongst a plurality of masks of known sizes and/orgeometries.

Finally, 48 the mask is then identified to the patient from amongst theplurality of masks to the patient and/or created, custom mask, and thenprovided to the patient. As an example, the patient may be provided withinformation, via any suitable form (e.g., electronically or viahardcopy), particularly specifying the mask (i.e., specifications whichparticularly identify the mask either from amongst other masks or how toconstruct from scratch or from components). For example, withoutlimitation, a prescription for obtaining a particular mask or a CAD fileor similar item containing instructions and/or dimensional informationfor constructing a custom mask. Alternatively, the mask may beidentified to the patient by providing the patient with the actual mask,be it custom-made or an off-the-shelf item. In the case of a custom-mademask, an output device, such as output device 26 of FIG. 2, in the formof a 3-D printer or other suitable automated manufacturing device may beused to provide the mask to the patient.

From the foregoing, it is to be appreciated that by taking intoconsideration plurality of facial positions as described in a pluralityof 2-D or 3-D images, embodiments of the present invention provide apatient with an all-around better fitting mask than conventionalsolutions.

Although the invention has been described in detail for the purpose ofillustration based on what is currently considered to be the mostpractical and preferred embodiments, it is to be understood that suchdetail is solely for that purpose and that the invention is not limitedto the disclosed embodiments, but, on the contrary, is intended to covermodifications and equivalent arrangements that are within the spirit andscope of the appended claims. For example, it is to be understood thatthe present invention contemplates that, to the extent possible, one ormore features of any embodiment can be combined with one or morefeatures of any other embodiment. It is also to be appreciated that theoverall and/or cross sectional shapes of structures described herein areprovided for exemplary purposes only and that such shapes may be variedwithout varying from the scope of the present invention.

In the claims, any reference signs placed between parentheses shall notbe construed as limiting the claim. The word “comprising” or “including”does not exclude the presence of elements or steps other than thoselisted in a claim. In a device claim enumerating several means, severalof these means may be embodied by one and the same item of hardware. Theword “a” or “an” preceding an element does not exclude the presence of aplurality of such elements. In any device claim enumerating severalmeans, several of these means may be embodied by one and the same itemof hardware. The mere fact that certain elements are recited in mutuallydifferent dependent claims does not indicate that these elements cannotbe used in combination.

What is claimed is:
 1. A method for identifying a mask for a patient,the method comprising: receiving a plurality of images of a patient'sface; analyzing the plurality of images to generate a temporal model ofthe patient's face; determining a mask for the patient using thetemporal model of the patient's face; and identifying the mask to thepatient.
 2. The method of claim 1, wherein identifying the mask to thepatient comprises providing the patient with a specification of themask, or the mask.
 3. The method of claim 1, wherein receiving aplurality of images comprises receiving a plurality of 3-D images of thepatient's face; and wherein analyzing the plurality of images comprisesgenerating the temporal model from the plurality of 3-D images.
 4. Themethod of claim 3, wherein the plurality of 3-D images comprises asequence of 3-D images captured over time.
 5. The method of claim 4,wherein analyzing the plurality of images comprises: determining anexpected range of facial geometries expressed by the patient's face;registering the range of facial geometries to create the temporal model;and determining an operating range of facial dimensions of the patient,wherein determining the appropriate mask for the patient based on theanalysis of the plurality of 3-D images comprises determining anappropriate mask for the patient based on the operating range of facialdimensions.
 6. The method of claim 1, wherein the temporal modelcomprises a range of facial dimensions and geometries of the patient'sface; and wherein determining a mask for the patient comprises comparingthe range of facial dimensions and geometries to establish an operatingrange of masks.
 7. The method of claim 1, wherein receiving a pluralityof images comprises receiving one or more 3-D images of the patient'sface and a plurality of 2-D images of the patient's face.
 8. The methodof claim 7, wherein analyzing the plurality of images comprises:generating a 3-D spatial model of the patient's face by analyzing theone or more 3-D images; and generating the temporal model of thepatient's face by registering the plurality of 2-D images to the 3-Dspatial model.
 9. The method of claim 8, further comprising: extractinginformation from the plurality of 2-D images, the information includingat least one: of landmarks, orientation, and features; and refining thegenerated 3-D spatial model using the extracted information.
 10. Themethod of claim 1, wherein receiving a plurality of images comprisesreceiving a plurality of 2-D images of the patient's face.
 11. Themethod of claim 10, wherein analyzing the plurality of images comprises:generating a plurality of 3-D models from the plurality of 2-D images byusing standard photogrammetric techniques or disparity maps; andgenerating the temporal model of the patient's face by registering the3-D models.
 12. The method of claim 1, wherein receiving a plurality ofimages comprises receiving a plurality of 2-D images of the patient'sface which each contain a reference object of known size; and whereinanalyzing the plurality of images comprises generating the temporalmodel of the patient's face using the plurality of 2-D images.
 13. Themethod of claim 1, wherein receiving a plurality of images comprisesreceiving a plurality of 2-D images of the patient's face, wherein each2-D image was captured with a known distance between a device used tocapture the 2-D image and the patient's face; and wherein analyzing theplurality of images comprises generating the spatial and temporal modelsof the patient's face using the plurality of 2-D images.
 14. A systemfor identifying a mask for a patient, the system comprising: aprocessing unit; and an output device in communication with theprocessing unit, wherein the processing unit is programmed to: receive aplurality of images of the patient's face; analyze the plurality ofimages to generate a temporal model of the patient's face; determine amask for the patient using the temporal model of the patient's face; andidentify the mask to the patient via the output device.
 15. The systemof claim 14, further comprising an image capturing device incommunication with the processing unit, the image capturing devicestructured to capture the plurality of images of the patient's face. 16.The system of claim 15, wherein the image capturing device comprises a3-D scanner.
 17. The system of claim 14, wherein the output devicecomprises a 3-D printer.